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Exploration of Sketch Models Quantifying VMT Kevin Fang 2017 ITE Institute

Exploration of Sketch Models Quantifying VMT Kevin Fang 2017 ITE Institute. NCST partners. Project overview. Funded by the California Strategic Growth Council Goal of building capacity among practitioners in the use of tools for estimating project-level VMT

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Exploration of Sketch Models Quantifying VMT Kevin Fang 2017 ITE Institute

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  1. Exploration of Sketch Models Quantifying VMTKevin Fang2017 ITE Institute

  2. NCST partners

  3. Project overview • Funded by the California Strategic Growth Council • Goal of building capacity among practitioners in the use of tools for estimating project-level VMT • Particularly for smart growth/infill-type projects • UC Davis Team: Susan Handy, Amy Lee, Kevin Fang

  4. Estimating VMT: Regional Models • Created by MPOs • Resource intensive:require modeling expertise andsometimes manydays to complete a single analysis Code included in a regionaltravel model setup guide

  5. “Sketch” models • Fill the need for less-resource intensive methods for localized plans and individual projects • Estimate VMT based off a smaller number of key inputs Sections of the GreenTrip Connect sketch tool input page

  6. Available tools • 12 tools initially identified by team • Expert panel meeting in May 2016

  7. Expert panel Chris Ganson Ron MilamJoe Castiglione Kelly CliftonClint Daniels Gordon GarryKaren Huss Cheryl LaskowskiGreg Newmark David OryRaef Porter Elizabeth SallJerry Walters Ron WestMaggie Witt Jillian Wong

  8. 6 Tools Selected for Further Analysis Web based tool Software programs Spreadsheets + map tool CaliforniaSmart Growth Trip Tool CalEEMod 2013 & 2016 Sketch7 MXD GreenTrip Connect Originally developedfor air quality/GHG analysis Developed for transportation/land use analysis

  9. Selected Methods:Applicable land uses

  10. Selected Methods:Applicable “contexts” Sacramento County, currently Sketch 7 Any context area CalEEMod GreenTrip Connect MXD “Smart growth”project location CA Smart GrowthTrip Generation Tool

  11. Calculating VMT Vehiclemiles traveled Numberof vehicle trips Average miles per trip × = ITE trip generation rates Trip lengths from regional model

  12. ITE-Estimated Vehicle-Tripsvs. Actual Vehicle-Trips At 30 smart growth sites in CA… • On average, ITE-estimates were 2.3 times higher than actual vehicle-trips in the AM peak • On average, ITE-estimates were 2.4 times higher than actual vehicle-trips in the PM peak • Schneider, R.J., K. Shafizadeh, B.R. Sperry, and S.L. Handy. “Methodology to Gather Multimodal Trip Generation Data in Smart-Growth Areas,” Transportation Research Record: Journal of the Transportation Research Board, Volume 2354, pp. 68-85, 2013.

  13. Adjustments for smart growth/infill Vehiclemiles traveled Numberof vehicle trips Average miles per trip × = Adjust trip rates Adjust trip lengths Adjust VMT estimates CA Smart Growth Trip Tool MXD GreenTrip Connect Sketch 7 CalEEMod

  14. Analysis of tools • Five case study projects • Applicable tools run foreach project • Tools report results indifferent units, converted to VMT per project per day • Also performed a sensitivity analysis testing a theoretical project at multiple locations

  15. Case Studies

  16. Case Study Projects

  17. The Cannery Residential, retail, commercial

  18. The Cannery Residential, retail, commercial

  19. Marea Alta Multi-family residential

  20. Marea Alta Multi-family residential

  21. Second Street Crossing Commercial

  22. Second Street Crossing Commercial +6,299 VMT per day within ½ mile

  23. How Sensitive are Tools to Context Area?

  24. Theoretical project

  25. Theoretical project

  26. Sensitivity Testing

  27. Key Lessons

  28. Ease of use • All of the methods have strengthsbut also drawbacks: • How easy to implement “off the shelf” • How easy to assemble data inputs • How easy to adjust parameters within the tool Part of CalEEMod traffic mitigation input window

  29. Tools vary in applicability • There is no “one-size-fits-all” method • Find the tool that best fits your particular need • Tailoring data inputs to be contextually sensitive is very important • Key input: trip lengths Example of project where CA Smart Growth Trip Tool is not applicable

  30. Validity • Noticeable variation in VMT projections for single projects among the different tools • Accuracy is uncertain for all methods given lack of validity testing so far • Even so, methods are useful for comparing alternative scenarios if same tool is used throughout

  31. Key lessons • Things to watch out for: • Project-based VMT, rather than project’s cumulative effect on VMT • Total VMT versus VMT per resident or employee • Models are new • As more practitioners make use of tools, we’ll learn more about strengths and weaknesses

  32. Additional Resources • Our draft full report is available here: https://ncst.ucdavis.edu/events/webinar-quantifying-vehicle-miles-traveled/ • UC Berkeley study on SB743 implementation for Caltrans: draft report under review • UC Davis project on GHG quantification methods for ARB starting late summer

  33. Thank you! Susan Handy slhandy@ucdavis.edu Amy Lee aelee@ucdavis.edu Kevin Fang kfang@ucdavis.edu Website: ncst.ucdavis.edu @NCST_research

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